Argentina v Austria · Oxford Football Forecasting

🇦🇷 Argentina CONMEBOL Elo 2,114 · world 2nd

61 / 26 / 13 win · draw · win most likely 1–0

🇦🇹 Austria UEFA Elo 1,830 · world 27th

Group: J
Date: Monday 22 June 2026
Kick-off: 17:00 UTC
Venue: Dallas Stadium, Arlington

§ 01

The scoreline grid

The ensemble's full distribution over exact scorelines — Argentina goals down the side, Austria goals across the top. This is the same 11×11 grid the tournament simulator samples.

Fig. V7 Ensemble · Group J

Argentina v Austria — scoreline probabilities

Cells show P(exact scoreline); the right column and bottom row are the marginal totals P(Argentina scores k) and P(Austria scores k). Grid runs 0–7 goals per side; the 8–10-goal tail holds 0.02% of the mass and is omitted from the cells (not from the totals).

The grid makes Argentina favourites at 61.4%, with a 26.1% draw. The single most-likely scoreline is 1–0 (17.0%), but no exact score clears 17% — the distribution is broad, as it should be.

Source · Oxford Football Forecasting model

§ 02

Result, goals & totals

The grid marginalised into the outcome split, expected goals each side, and the goal-total markets — every figure read straight off the same distribution.

Win · draw · loss

61.4% 26.1% 12.5%

🇦🇷 Argentina 61.4% Draw 26.1% 🇦🇹 Austria 12.5%

Rounded values sum to exactly 100%.

Expected goals (λ)

🇦🇷Argentina 1.61

🇦🇹Austria 0.59

Poisson means feeding the grid; combined expected goals 2.20.

37.7% Over 2.5 goals P(3 or more goals in the match)

62.3% Under 2.5 goals complement of over-2.5

36.5% Both teams to score P(each side scores ≥ 1)

1–0 Most-likely scoreline modal exact score · 17.0%

§ 03

Venue context

The conditions at Dallas Stadium, Arlington — the same environment layer the dossiers' climate exposure draws on.

AT&T Arlington, USA

Heat index 45°C apparent temperature (June–July)

Max temperature 35°C June–July daily high

Humidity 62% relative humidity

Altitude 177m above sea level

Source · Open-Meteo & venue records. Travel and time-zone exposure are per-team — see each side's dossier.

§ 04

Why the model leans this way

The inputs behind the grid — each side's strength signals laid side by side. The forecast is the ensemble's, not a hand-weighting of these; this panel is the descriptive read.

2,114 Elo rating 1,830

2.47 Recent NT form 2.20

€946M Squad value €281M

0.330 Squad form (global) 0.149

0.785 Fitness readiness 0.785

+0.21 Decoupling g +0.31

Argentina carry the Elo edge (284 points). On the decoupling axis, Austria is the side whose squad is valued higher relative to its record.

How a single-match forecast is built

The pairing is scored by the ensemble — Dixon-Coles bivariate-Poisson, the Bayesian hierarchical model and the global LightGBM-Poisson, log-pooled — yielding the 11×11 scoreline grid above. Win/draw/loss, expected goals (λ), over-2.5 and both-teams-to-score are all marginals of that one grid, so they are mutually consistent by construction. The strength inputs shown here feed the models; the forecast is their pooled output, not a manual weighting of these rows. The model matches the market out-of-sample (RPS 0.1891 vs 0.1905); it does not significantly beat it at n = 3. The ensemble, in full →